I have an emotion database of 213 (with 7 classes). I used a bank of Gabor filters for the extraction of features. So I got a data matrix of 213x50000 (a huge number of parameters on only 213 images !!). So i have to reduce this large number of features before learning with SVM, and i decided to reduce with PCA. Is it a good choice?